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Healthy minds 0–100 years: Optimising the use of European brain imaging cohorts (“Lifebrain”)

  • Kristine B. Walhovd (a1), Anders M. Fjell (a1), René Westerhausen (a1), Lars Nyberg (a2), Klaus P. Ebmeier (a3), Ulman Lindenberger (a4), David Bartrés-Faz (a5), William F.C. Baaré (a6), Hartwig R. Siebner (a6), Richard Henson (a7), Christian A. Drevon (a8), Gun Peggy Strømstad Knudsen (a9), Isabelle Budin Ljøsne (a9), Brenda W.J.H. Penninx (a10), Paolo Ghisletta (a11) (a12), Ole Rogeberg (a13), Lorraine Tyler (a14), Lars Bertram (a15) and Lifebrain Consortium...


The main objective of “Lifebrain” is to identify the determinants of brain, cognitive and mental (BCM) health at different stages of life. By integrating, harmonising and enriching major European neuroimaging studies across the life span, we will merge fine-grained BCM health measures of more than 5000 individuals. Longitudinal brain imaging, genetic and health data are available for a major part, as well as cognitive and mental health measures for the broader cohorts, exceeding 27,000 examinations in total. By linking these data to other databases and biobanks, including birth registries, national and regional archives, and by enriching them with a new online data collection and novel measures, we will address the risk factors and protective factors of BCM health. We will identify pathways through which risk and protective factors work and their moderators. Exploiting existing European infrastructures and initiatives, we hope to make major conceptual, methodological and analytical contributions towards large integrative cohorts and their efficient exploitation. We will thus provide novel information on BCM health maintenance, as well as the onset and course of BCM disorders. This will lay a foundation for earlier diagnosis of brain disorders, aberrant development and decline of BCM health, and translate into future preventive and therapeutic strategies. Aiming to improve clinical practice and public health we will work with stakeholders and health authorities, and thus provide the evidence base for prevention and intervention.

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[1]Gustavsson, ASvensson, MJacobi, FAllgulander, CAlonso, JBeghi, E et al. Cost of disorders of the brain in Europe 2010. Eur Neuropsychopharmacol 2011;21(10):718–79.
[2]Habib, RNyberg, LNilsson, LGCognitive and non-cognitive factors contributing to the longitudinal identification of successful older adults in the betula study. Neuropsychol Dev Cogn B Aging Neuropsychol Cogn 2007;14(3):257–73.
[3]Nevalainen, NRiklund, KAndersson, MAxelsson, JOgren, MLovden, M et al. COBRA: a prospective multimodal imaging study of dopamine, brain structure and function, and cognition. Brain Res 2015; 1612:83103.
[4]Filippini, NZsoldos, EHaapakoski, RSexton, CEMahmood, AAllan, CL et al. Study protocol: the Whitehall II imaging sub-study. BMC Psychiatry 2014; 14:159.
[5]Gathercole, SEWoolgar, FTeam, CKievit, RAAstle, DManly, T et al. How common are WM deficits in children with difficulties in reading and mathematics?. J Appl Res Mem Cogn 2016;5(4):384–94.
[6]Taylor, JRWilliams, NCusack, RAuer, TShafto, MADixon, M et al. The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) data repository: structural and functional MRI, MEG, and cognitive data from a cross-sectional adult lifespan sample. Neuroimage 144(Pt B)2017; 262–69.
[7]Hulur, GDrewelies, JEibich, PDuzel, SDemuth, IGhisletta, P et al. Cohort differences in psychosocial function over 20 years: current older adults feel less lonely and less dependent on external circumstances. Gerontology 2016;62(3):354–61.
[8]Fjell, AMSneve, MHGrydeland, HStorsve, ABAmlien, IKYendiki, A et al. Relationship between structural and functional connectivity change across the adult lifespan: a longitudinal investigation. Hum Brain Mapp 2017;38(1):561–73.
[9]Dijkstra-Kersten, SMASitnikova, KTerluin, BPenninx, BTwisk, JWRvan Marwijk, HWJ et al. Longitudinal associations of multiple physical symptoms with recurrence of depressive and anxiety disorders. J Psychosom Res 2017; 97:96101.
[10]Madsen, KSBaare, WFSkimminge, AVestergaard, MSiebner, HRJernigan, TLBrain microstructural correlates of visuospatial choice reaction time in children. Neuroimage 2011;58(4):1090–100.
[11]Ramsoy, TZLiptrot, MGSkimminge, ALund, TESidaros, KChristensen, MS et al. Healthy aging attenuates task-related specialization in the human medial temporal lobe. Neurobiol Aging 2012;33(9):1874–89.
[12]Maneru, CJunque, CSalgado-Pineda, PSerra-Grabulosa, JMBartres-Faz, DRamirez-Ruiz, B et al. Corpus callosum atrophy in adolescents with antecedents of moderate perinatal asphyxia. Brain Inj 2003;17(11):1003–9.
[13]Engvig, AFjell, AMWestlye, LTMoberget, TSundseth, OLarsen, VA et al. Effects of memory training on cortical thickness in the elderly. Neuroimage 2010;52(4):1667–76.
[14]Ngandu, TLehtisalo, JSolomon, ALevalahti, EAhtiluoto, SAntikainen, R et al. A 2 year multidomain intervention of diet, exercise, cognitive training, and vascular risk monitoring versus control to prevent cognitive decline in at-risk elderly people (FINGER): a randomised controlled trial. Lancet 2015;385(9984):2255–63.
[15]Beekman, ATCopeland, JRPrince, MJReview of community prevalence of depression in later life. Br J Psychiatry 1999; 174:307–11.
[16]Schweizer, SKievit, RAEmery, TCam, CANHenson, RNSymptoms of depression in a large healthy population cohort are related to subjective memory complaints and memory performance in negative contexts. Psychol Med 2017; 111.
[17]Skirbekk, VLoichinger, EWeber, DVariation in cognitive functioning as a refined approach to comparing aging across countries. Proc Natl Acad Sci U S A 2012;109(3):770–4.
[18]Weber, DSkirbekk, VFreund, IHerlitz, AThe changing face of cognitive gender differences in Europe. Proc Natl Acad Sci U S A 2014;111(32):11673–78.
[19]Brandmaier, AMvon Oertzen, TMcArdle, JJLindenberger, UStructural equation model trees. Psychol Methods 2013;18(1):7186.
[20]Josefsson, Mde Luna, XPudas, SNilsson, LGNyberg, LGenetic and lifestyle predictors of 15-year longitudinal change in episodic memory. J Am Geriatr Soc 2012;60(12):2308–12.
[21]Abel, KMWicks, SSusser, ESDalman, CPedersen, MGMortensen, PB et al. Birth weight, schizophrenia, and adult mental disorder: is risk confined to the smallest babies?. Arch Gen Psychiatry 2010;67(9):923–30.
[22]Tuovinen, SEriksson, JGKajantie, ELahti, JPesonen, AKHeinonen, K et al. Maternal hypertensive disorders in pregnancy and self-reported cognitive impairment of the offspring 70 years later: the Helsinki Birth Cohort Study. Am J Obstet Gynecol 2013;208(3):200 e1-9.
[23]Aizer, ACurrie, JThe intergenerational transmission of inequality: maternal disadvantage and health at birth. Science 2014;344(6186):856–61.
[24]Ross, MGDesai, MKhorram, OMcKnight, RALane, RHTorday, JGestational programming of offspring obesity: a potential contributor to Alzheimer's disease. Curr Alzheimer Res 2007;4(2):213–17.
[25]Syddall, HESayer, AASimmonds, SJOsmond, CCox, VDennison, EM et al. Birth weight, infant weight gain, and cause-specific mortality: the Hertfordshire Cohort Study. Am J Epidemiol 2005;161(11):1074–80.
[26]Walhovd, KBTamnes, CKFjell, AMBrain structural maturation and the foundations of cognitive behavioral development. Curr Opin Neurol 2014;27(2):176–84.
[27]Walhovd, KBFjell, AMBrown, TTKuperman, JMChung, YHagler, DJ Jr. et al. Long-term influence of normal variation in neonatal characteristics on human brain development. Proc Natl Acad Sci U S A 2012;109(49):20089–94.
[28]Fjell, AMWalhovd, KBBrown, TTKuperman, JMChung, YHagler, DJ Jr. et al. Multimodal imaging of the self-regulating developing brain. Proc Natl Acad Sci U S A 2012;109(48):19620–5.
[29]Knickmeyer, RCWang, JZhu, HGeng, XWoolson, SHamer, RM et al. Common variants in psychiatric risk genes predict brain structure at birth. Cereb Cortex 2014;24(5):1230–46.
[30]Ho, AJStein, JLHua, XLee, SHibar, DPLeow, AD et al. A commonly carried allele of the obesity-related FTO gene is associated with reduced brain volume in the healthy elderly. Proc Natl Acad Sci U S A 2010;107(18):8404–9.
[31]Reitz, CTosto, GMayeux, RLuchsinger, JAN-LNFS Group, Alzheimer's disease neuroimaging I. Genetic variants in the fat and obesity associated (FTO) gene and risk of Alzheimer's disease. PLoS One 2012;7(12):e50354.
[32]Milaneschi, YLamers, FMbarek, HHottenga, JJBoomsma, DIPenninx, BWThe effect of FTO rs9939609 on major depression differs across MDD subtypes. Mol Psychiatry 2014;19(9):960–62.
[33]Melka, MGGillis, JBernard, MAbrahamowicz, MChakravarty, MMLeonard, GT et al. FTO, obesity and the adolescent brain. Hum Mol Genet 2013;22(5):1050–58.
[34]Deary, IJPattie, AStarr, JMThe stability of intelligence from age 11 to age 90 years: the Lothian birth cohort of 1921. Psychol Sci 2013;24(12):2361–8.
[35]Hakulinen, CElovainio, MPulkki-Raback, LVirtanen, MKivimaki, MJokela, MPersonality and depressive symptoms individual participant meta-analysis of 10 cohort studies. Depress Anxiety 2015;32(7):461–70.
[36]Nyberg, JAberg, MASchioler, LNilsson, MWallin, AToren, K et al. Cardiovascular and cognitive fitness at age 18 and risk of early-onset dementia. Brain 137(Pt 5)2014; 1514–23.
[37]Walhovd, KBStorsve, ABWestlye, LTDrevon, CAFjell, AMBlood markers of fatty acids and vitamin D, cardiovascular measures, body mass index, and physical activity relate to longitudinal cortical thinning in normal aging. Neurobiol Aging 2014;35(5):1055–64.
[38]Sabia, SDugravot, ADartigues, JFAbell, JElbaz, AKivimaki, M et al. Physical activity, cognitive decline, and risk of dementia: 28 year follow-up of Whitehall II cohort study. BMJ 2017; 357:j2709.
[39]Batsis, JASingh, SLopez-Jimenez, FAnthropometric measurements and survival in older Americans: results from the third National Health and Nutrition Examination Survey. J Nutr Health Aging 2014;18(2):123–30.
[40]Sundstrom, AMarklund, PNilsson, LGCruts, MAdolfsson, RVan Broeckhoven, C et al. APOE influences on neuropsychological function after mild head injury: within-person comparisons. Neurology 2004;62(11):1963–6.
[41]Ghisletta, PBackman, LBertram, LBrandmaier, AMGerstorf, DLiu, T et al. The Val/Met polymorphism of the brain-derived neurotrophic factor (BDNF) gene predicts decline in perceptual speed in older adults. Psychol Aging 2014;29(2):384–92.
[42]Hosang, GMShiles, CTansey, KEMcGuffin, PUher, RInteraction between stress and the BDNF Val66Met polymorphism in depression: a systematic review and meta-analysis. BMC Med 2014; 12:7.
[43]Lindenberger, UNagel, IEChicherio, CLi, SCHeekeren, HRBackman, LAge-related decline in brain resources modulates genetic effects on cognitive functioning. Front Neurosci 2008;2(2):234–44.
[44]Papenberg, GLindenberger, UBackman, LAging-related magnification of genetic effects on cognitive and brain integrity. Trends Cogn Sci 2015;19(9):506–14.
[45]Hanamsagar, RBilbo, SDSex differences in neurodevelopmental and neurodegenerative disorders: focus on microglial function and neuroinflammation during development. J Steroid Biochem Mol Biol 2016; 160:127–33.
[46]Loke, HHarley, VLee, JBiological factors underlying sex differences in neurological disorders. Int J Biochem Cell Biol 2015; 65:139–50.
[47]Solomon, MBHerman, JPSex differences in psychopathology: of gonads, adrenals and mental illness. Physiol Behav 2009;97(2):250–8.
[48]Riedel, BCThompson, PMBrinton, RDAge, APOE and sex. Triad of risk of Alzheimer's disease. J Steroid Biochem Mol Biol 2016; 160:134–47.
[49]Ingalhalikar, MSmith, AParker, DSatterthwaite, TDElliott, MARuparel, K et al. Sex differences in the structural connectome of the human brain. Proc Natl Acad Sci U S A 2014;111(2):823–8.
[50]Joel, DBerman, ZTavor, IWexler, NGaber, OStein, Y et al. Sex beyond the genitalia: the human brain mosaic. Proc Natl Acad Sci U S A 2015;112(50):15468–73.
[51]Mendrek, AIs it important to consider sex and gender in neurocognitive studies?. Front Psychiatry 2015; 6:83.
[52]Bale, TLEpperson, CNSex differences and stress across the lifespan. Nat Neurosci 2015;18(10):1413–20.
[53]Kendler, KSEdwards, ACGardner, COSex differences in the pathways to symptoms of alcohol use disorder: a study of opposite-sex twin pairs. Alcohol Clin Exp Res 2015;39(6):9981007.
[54]Helland, IBSmith, LSaarem, KSaugstad, ODDrevon, CAMaternal supplementation with very-long-chain n-3 fatty acids during pregnancy and lactation augments children's IQ at 4 years of age. Pediatrics 2003;111(1):e3944.
[55]Henriksen, CHaugholt, KLindgren, MAurvag, AKRonnestad, AGronn, M et al. Improved cognitive development among preterm infants attributable to early supplementation of human milk with docosahexaenoic acid and arachidonic acid. Pediatrics 2008;121(6):1137–45.
[56]Etgen, TSander, DBickel, HSander, KForstl, HVitamin D deficiency, cognitive impairment and dementia: a systematic review and meta-analysis. Dement Geriatr Cogn Disord 2012;33(5):297305.
[57]de Koning, EJvan Schoor, NMPenninx, BWElders, PJHeijboer, ACSmit, JH et al. Vitamin D supplementation to prevent depression and poor physical function in older adults: study protocol of the D-Vitaal study, a randomized placebo-controlled clinical trial. BMC Geriatr 2015; 15:151.
[58]de Luis, DAAller, RConde, RIzaola, OGonzalez Sagrado, MCastrodeza Sanz, JThe rs9939609 gene variant in FTO modified the metabolic response of weight loss after a 3-month intervention with a hypocaloric diet. J Investig Med 2013;61(1):22–6.
[59]Skoog, IWaern, MDuberstein, PBlennow, KZetterberg, HBorjesson-Hanson, A et al. A 9-year prospective population-based study on the association between the APOE*E4 allele and late-life depression in Sweden. Biol Psychiatry 2015;78(10):730–6.
[60]Hita-Yanez, EAtienza, MGil-Neciga, ECantero, JLDisturbed sleep patterns in elders with mild cognitive impairment: the role of memory decline and ApoE epsilon4 genotype. Curr Alzheimer Res 2012;9(3):290–7.
[61]Sexton, CEStorsve, ABWalhovd, KBJohansen-Berg, HFjell, AMPoor sleep quality is associated with increased cortical atrophy in community-dwelling adults. Neurology 2014;83(11):967–73.
[62]Sexton, CEZsoldos, EFilippini, NGriffanti, LWinkler, AMahmood, A et al. Associations between self-reported sleep quality and white matter in community-dwelling older adults: a prospective cohort study. Hum Brain Mapp 2017.
[63]Branger, PArenaza-Urquijo, EMTomadesso, CMezenge, FAndre, Cde Flores, R et al. Relationships between sleep quality and brain volume, metabolism, and amyloid deposition in late adulthood. Neurobiol Aging 2016; 41:107–14.
[64]Brown, BMPeiffer, JJTaddei, KLui, JKLaws, SMGupta, VB et al. Physical activity and amyloid-beta plasma and brain levels: results from the Australian imaging, biomarkers and lifestyle study of ageing. Mol Psychiatry 2013;18(8):875–81.
[65]Gardener, SLRainey-Smith, SRBarnes, MBSohrabi, HRWeinborn, MLim, YY et al. Dietary patterns and cognitive decline in an Australian study of ageing. Mol Psychiatry 2015;20(7):860866.
[66]Wang, HXGustafson, DRKivipelto, MPedersen, NLSkoog, IWindblad, B et al. Education halves the risk of dementia due to apolipoprotein epsilon4 allele: a collaborative study from the Swedish brain power initiative. Neurobiol Aging 2012;33(5):1007 e1-7.
[67]Vemuri, PLesnick, TGPrzybelski, SAKnopman, DSMachulda, MLowe, VJ et al. Effect of intellectual enrichment on AD biomarker trajectories: longitudinal imaging study. Neurology 2016;86(12):11281135.
[68]Arenaza-Urquijo, EMGonneaud, JFouquet, MPerrotin, AMezenge, FLandeau, B et al. Interaction between years of education and APOE epsilon4 status on frontal and temporal metabolism. Neurology 2015;85(16):13921399.
[69]Pudas, SPersson, JJosefsson, Mde Luna, XNilsson, LGNyberg, LBrain characteristics of individuals resisting age-related cognitive decline over two decades. J Neurosci 2013;33(20):86688677.
[70]Ekman, UEriksson, JForsgren, LMo, SJRiklund, KNyberg, LFunctional brain activity and presynaptic dopamine uptake in patients with Parkinson's disease and mild cognitive impairment: a cross-sectional study. Lancet Neurol 2012;11(8):679687.
[71]Suri, STopiwala, AFilippini, NZsoldos, EMahmood, ASexton, CE et al. Distinct resting-state functional connections associated with episodic and visuospatial memory in older adults. Neuroimage 2017; 159:122130.
[72]Wikgren, MKarlsson, TNilbrink, TNordfjall, KHultdin, JSleegers, K et al. APOE epsilon4 is associated with longer telomeres, and longer telomeres among epsilon4 carriers predicts worse episodic memory. Neurobiol Aging 2012;33(2):335344.
[73]Nyberg, LSalami, AAndersson, MEriksson, JKalpouzos, GKauppi, K et al. Longitudinal evidence for diminished frontal cortex function in aging. Proc Natl Acad Sci U S A 2010;107(52):2268222686.
[74]Doiron, DBurton, PMarcon, YGaye, AWolffenbuttel, BHRPerola, M et al. Data harmonization and federated analysis of population-based studies: the BioSHaRE project. Emerg Themes Epidemiol 2013;10(1):12.
[75]Amlien, IKFjell, AMDiffusion tensor imaging of white matter degeneration in Alzheimer's disease and mild cognitive impairment. Neuroscience 2014; 276:206215.
[76]Yendiki, AReuter, MWilkens, PRosas, HDFischl, BJoint reconstruction of white-matter pathways from longitudinal diffusion MRI data with anatomical priors. Neuroimage 2016; 127:277286.
[77]Hibar, DPStein, JLRenteria, MEArias-Vasquez, ADesrivieres, SJahanshad, N et al. Common genetic variants influence human subcortical brain structures. Nature 2015;520(7546):224229.
[78]Fjell, AMWalhovd, KBFennema-Notestine, CMcEvoy, LKHagler, DJHolland, D et al. Brain atrophy in healthy aging is related to CSF levels of Abeta1-42. Cereb Cortex 2010;20(9):20692079.
[79]Walhovd, KBFjell, AMBrewer, JMcEvoy, LKFennema-Notestine, CHagler, DJ Jr. et al. Combining MR imaging, positron-emission tomography, and CSF biomarkers in the diagnosis and prognosis of Alzheimer disease. Am J Neuroradiol 2010;31(2):347354.
[80]Fjell, AMWestlye, LTAmlien, IEspeseth, TReinvang, IRaz, N et al. High consistency of regional cortical thinning in aging across multiple samples. Cereb Cortex 2009;19(9):20012012.
[81]Han, XJovicich, JSalat, Dvan der Kouwe, AQuinn, BCzanner, S et al. Reliability of MRI-derived measurements of human cerebral cortical thickness: the effects of field strength, scanner upgrade and manufacturer. Neuroimage 2006;32(1):180194.
[82]Han, XFischl, BAtlas renormalization for improved brain MR image segmentation across scanner platforms. IEEE Trans Med Imaging 2007;26(4):479486.
[83]Douaud, GRefsum, Hde Jager, CAJacoby, RNichols, TESmith, SM et al. Preventing Alzheimer's disease-related gray matter atrophy by B-vitamin treatment. Proc Natl Acad Sci U S A 2013;110(23):95239528.
[84]Brandmaier, AMPrindle, JJMcArdle, JJLindenberger, UTheory-guided exploration with structural equation model forests. Psychol Methods 2016;21(4):566582.
[85]Hertzog, CLindenberger, UGhisletta, POertzen, TOn the power of multivariate latent growth curve models to detect correlated change. Psychol Methods 2006;11(3):244252.
[86]von Oertzen, TPower equivalence in structural equation modelling. Br J Math Stat Psychol 63(Pt 2)2010; 257272.
[87]von Oertzen, THertzog, CLindenberger, UGhisletta, PThe effect of multiple indicators on the power to detect inter-individual differences in change. Br J Math Stat Psychol 63(Pt 3)2010; 627646.
[88]von Oertzen, TBrandmaier, AMOptimal study design with identical power: an application of power equivalence to latent growth curve models. Psychol Aging 2013;28(2):414428.
[89]Brandmaier, AMvon Oertzen, TGhisletta, PHertzog, CLindenberger, ULifespan, A tool for the computer-aided design of longitudinal studies. Front Psychol 2015; 6:272.
[90]Livingston, GSommerlad, AOrgeta, VCostafreda, SGHuntley, JAmes, D et al. Dementia prevention, intervention, and care. Lancet 2017.


Healthy minds 0–100 years: Optimising the use of European brain imaging cohorts (“Lifebrain”)

  • Kristine B. Walhovd (a1), Anders M. Fjell (a1), René Westerhausen (a1), Lars Nyberg (a2), Klaus P. Ebmeier (a3), Ulman Lindenberger (a4), David Bartrés-Faz (a5), William F.C. Baaré (a6), Hartwig R. Siebner (a6), Richard Henson (a7), Christian A. Drevon (a8), Gun Peggy Strømstad Knudsen (a9), Isabelle Budin Ljøsne (a9), Brenda W.J.H. Penninx (a10), Paolo Ghisletta (a11) (a12), Ole Rogeberg (a13), Lorraine Tyler (a14), Lars Bertram (a15) and Lifebrain Consortium...


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Healthy minds 0–100 years: Optimising the use of European brain imaging cohorts (“Lifebrain”)

  • Kristine B. Walhovd (a1), Anders M. Fjell (a1), René Westerhausen (a1), Lars Nyberg (a2), Klaus P. Ebmeier (a3), Ulman Lindenberger (a4), David Bartrés-Faz (a5), William F.C. Baaré (a6), Hartwig R. Siebner (a6), Richard Henson (a7), Christian A. Drevon (a8), Gun Peggy Strømstad Knudsen (a9), Isabelle Budin Ljøsne (a9), Brenda W.J.H. Penninx (a10), Paolo Ghisletta (a11) (a12), Ole Rogeberg (a13), Lorraine Tyler (a14), Lars Bertram (a15) and Lifebrain Consortium...
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